Indoor environments normally contain rich semantic information which can be used to guide the exploration. In this paper, we study this by detecting doors as semantic objects and classifying frontiers to help the exploration behavioral planning.
Unlike [1]}, [2]}, which detect doors from laser scans, we directly detect doors from occupancy maps around frontier clusters. This allows the detection to happen in parallel at all frontier clusters.
